InterviewSignal – open-source AI-native technical interviews
Grades how candidates use AI, not just their output—finally addresses the AI-cheating problem.

$0.99per interview undercuts enterprise tools, but LLM-as-interviewer is a crowded category.
Recruiting teams and hiring managers looking to reduce manual screening burden.
Pymetrics · HireEQ · Paradox
I am Mukul, and my co-founder Tushar and I built InterviewFlowAI (https://interviewflowai.com) to conduct conversational first-round screening interviews over phone or video.
We built this because manual phone screening is broken, especially with the current flood of AI generated resumes. Existing tools require massive enterprise contracts, so we made ours strictly $0.99 per interview.
The hardest engineering challenge was not hooking up text-to-speech. It was optimizing our system prompts so the LLM actually probes for depth. If a candidate gives a vague answer, the AI dynamically asks for specifics before generating a structured scorecard.
Our stack is React JS, Supabase, and AWS. We just crossed our first 100 users and are working hard to keep voice latency low while running these complex background evaluations.
We would love for you to tear it apart. Any feedback on the dashboard UX or how natural the interview flow feels would be amazing.
Grades how candidates use AI, not just their output—finally addresses the AI-cheating problem.
Polished product, but recruiter bots and warm intro networks already solve this.
No GitHub account or repo setup — candidates get a link and review code immediately.
Yet another interview scorecard, but at least nothing leaves your browser.
macOS screen-capture exclusion keeps the overlay invisible to Zoom and interviewers.
Automates 40% of recruiter workload; Claude+ElevenLabs pipeline handles flow that plagued Paradox, Pinecone.